Random numbers have found valuable applications in many fields such as cryptography, games of chance, scientific calculus and/or statistical studies. In these applications, the randomness of the generated random numbers is of great importance since their predictability can lead to unsecure communication, to cheating and/or unreliable scientific results, for instance.
Characteristics which are sought from random number generators include the ability to produce random numbers at a relatively high rate while using devices which are relatively accessible in terms of pricing, bulkiness, etc.
To satisfy these needs, the methods formerly used typically relied on pseudo-random algorithms and/or pseudo-random physical properties of materials. While random numbers generated by such methods may seem completely random at first glance (they may even pass the statistical test suite for random number generators of the National Institute of Standards and Technology (NIST)), such pseudo-random generators are often based on deterministic approaches and can thus have a flaw which can allow predicting the results if the flaw is ultimately discovered.
There thus remained room for improvement in providing a suitable device for producing random number generation.